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      <title>Kafka是怎么保证消息可靠性的？ - 交互式测验</title>
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              <h1>Kafka是怎么保证消息可靠性的？ - 交互式测验</h1>
              <p>检验你对文档内容的理解程度</p>
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  {
    "question": "在Kafka生产者的消息确认机制中，当设置 `acks=all` 时，以下哪个描述是正确的？",
    "options": [
      "生产者发送消息后，无需等待任何来自Broker的确认。",
      "只有分区的Leader副本成功接收并写入消息后，生产者就会收到确认。",
      "Leader副本以及所有处于ISR（In-Sync Replica）集合中的Follower副本都成功写入消息后，生产者才会收到确认。",
      "Leader副本和所有Follower副本（无论是否在ISR中）都确认消息后，生产者才会收到确认。"
    ],
    "correctAnswerIndex": 2,
    "explanation": "`acks=all`（或-1）提供了最高等级的消息可靠性保证。在这种模式下，生产者发送的消息不仅需要被Leader副本成功写入，还必须等待所有处于同步状态（ISR）的Follower副本都成功复制了该消息后，才会向生产者发送确认。这确保了即使Leader副本发生故障，消息也已经存在于至少一个同步的Follower副本中，不会丢失。",
    "source": "文档中「生产者发送消息」部分的“消息确认机制”",
    "hint": "文档中对三种确认机制进行了描述，思考 `acks=all` 是如何提供最高级别保障的。"
  },
  {
    "question": "根据文档，Kafka中的ISR（In-Sync Replica）机制主要作用是什么？",
    "options": [
      "用于存储那些暂时无法被消费的消息。",
      "它是一个包含了所有副本（包括落后的副本）的集合，用于选举新的Leader。",
      "它是一个包含了与Leader副本保持数据同步的副本集合，用于保证数据一致性和故障转移。",
      "专门用来管理消费者组的偏移量提交。"
    ],
    "correctAnswerIndex": 2,
    "explanation": "ISR（In-Sync Replica）是Kafka可靠性设计的核心。它维护了一个与Leader副本保持良好同步状态的Follower副本列表。只有ISR集合中的副本才有资格参与消息的读写确认和被选举为新的Leader。如果一个Follower副本落后Leader太多，它将被从ISR中移除，从而保证了被确认的消息一定存在于多个同步的副本上，增强了数据的一致性和系统的容错能力。",
    "source": "文档中「消息复制」部分的“ISR（In-Sync Replica）机制”",
    "hint": "思考ISR中的“In-Sync”代表了什么状态，以及这个状态对于副本的功能有何影响。"
  },
  {
    "question": "当一个分区的Leader副本发生故障时，Kafka会如何进行故障转移以保证服务的可用性？",
    "options": [
      "系统会暂停该分区的服务，直到原Leader副本恢复。",
      "Kafka会从ISR（In-Sync Replicas）集合中选择一个健康的Follower副本，并将其晋升为新的Leader。",
      "生产者会随机选择一个Follower副本作为新的Leader继续发送消息。",
      "系统会自动创建一个全新的Broker来接管Leader的角色。"
    ],
    "correctAnswerIndex": 1,
    "explanation": "Kafka的故障转移机制是自动的。当检测到Leader副本故障时，控制器会从与该Leader保持同步的ISR集合中选举一个新的Leader。因为ISR中的副本数据与旧Leader的数据是最接近甚至完全一致的，所以从中选择新Leader可以最大程度地保证消息不丢失，并快速恢复分区的读写服务，从而实现高可用性。",
    "source": "文档中「故障转移」部分的“Follower副本晋升”",
    "hint": "文档提到，当Leader失效时，会从一个特定的集合中选择新的Leader，这个集合的成员有什么特点？"
  },
  {
    "question": "为了保证消费者在发生故障或重启后能够从正确的位置继续消费，Kafka依赖于哪项关键机制？",
    "options": [
      "消费者组的重平衡（Rebalancing）机制。",
      "Kafka Broker的消息持久化机制。",
      "消费者对消费位置（Offset）的管理和提交。",
      "生产者的消息重试机制。"
    ],
    "correctAnswerIndex": 2,
    "explanation": "Kafka通过偏移量（Offset）来精确追踪每个消费者组在每个分区上的消费进度。消费者在处理完消息后，会定期向Kafka提交（commit）当前消费到的Offset。当消费者崩溃重启或新的消费者加入时，它可以通过读取上一次提交的Offset，从上次中断的位置继续消费，从而避免了重复消费或丢失消息的问题。",
    "source": "文档中「消费者」部分的“偏移量的管理”",
    "hint": "想一想，消费者是如何“记住”自己读到哪里了的？"
  },
  {
    "question": "根据文档描述，Kafka是如何实现消息的持久化以防止数据丢失的？",
    "options": [
      "将消息实时写入外部的关系型数据库中。",
      "消息被写入操作系统的页缓存，然后由操作系统异步地刷写到磁盘文件中。",
      "消息只保存在Broker的内存中，以获得极高的性能。",
      "消息由生产者负责保存，直到消费者确认消费为止。"
    ],
    "correctAnswerIndex": 1,
    "explanation": "Kafka的持久化策略依赖于操作系统的文件系统。当消息到达Broker后，会首先被写入到操作系统的页缓存（Page Cache）中，这个过程非常快。然后，操作系统会根据自身的策略将页缓存中的数据异步地刷写（flush）到物理磁盘上。这种方式结合了内存的高速读写和磁盘的持久化能力，即使Broker进程崩溃，只要操作系统正常，页缓存中的数据通常不会丢失，重启后仍可恢复。",
    "source": "文档中「消息复制和持久化」部分的“持久化”",
    "hint": "文档中提到消息持久化依赖于磁盘，并且这个过程是“异步刷写”的，它首先被写入了哪里？"
  },
  {
    "question": "在Kafka的消息复制流程中，Leader副本将消息同步给Follower副本的过程是同步的还是异步的？",
    "options": [
      "完全同步的，Leader必须等待所有Follower确认后才能写入自己的本地日志。",
      "异步的，Leader将消息写入本地日志后，会异步地将消息复制给Follower，不直接等待它们的确认。",
      "这是一个可配置的选项，可以是同步也可以是异步。",
      "对于ISR内的Follower是同步的，对于ISR外的Follower是异步的。"
    ],
    "correctAnswerIndex": 1,
    "explanation": "文档中明确指出：“Leader副本将已经写入本地日志的消息同步（复制）到所有的Follower副本。这是一个异步的过程，Leader会将消息发送给Followers，但不会等待它们的确认。” Leader首先确保消息写入了自己的本地日志（这是一个同步过程），然后异步地将这些日志条目发送给Follower副本进行复制。Follower复制成功后，会反过来向Leader发送确认。",
    "source": "文档中「Leader 副本写入」部分的“Leader副本同步到Followers”",
    "hint": "文档描述了Leader副本写入本地日志后的下一步操作，请关注该操作的执行方式。"
  }
];
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                '<div class="score-card score-details">' +
                '<table>' +
                '<tr><td>正确</td><td>' + correctCount + '</td></tr>' +
                '<tr><td>错误</td><td>' + wrongCount + '</td></tr>' +
                '<tr><td>未答</td><td>' + skippedCount + '</td></tr>' +
                '</table>' +
                '</div>' +
                '</div>' +
                '<div class="report-actions">' +
                '<button id="review-btn">回顾测验</button>' +
                '<button class="primary" onclick="location.reload()">再试一次</button>' +
                '</div>' +
                '</div>';

            let reportEl = document.querySelector('.final-score-container');
            if (reportEl) {
                reportEl.remove();
            }
            quizContentEl.insertAdjacentHTML('beforeend', finalScoreHtml);
            document.getElementById('review-btn').addEventListener('click', reviewQuiz);
        }

        function reviewQuiz() {
            const reportEl = document.querySelector('.final-score-container');
            if (reportEl) {
                reportEl.remove();
            }

            document.querySelector('.quiz-body').style.display = 'block';
            document.getElementById('quiz-footer').style.display = 'flex';
            
            currentQuestionIndex = 0;
            loadQuestion();
            updateNavigationButtons(); // Ensure nav buttons are correctly displayed
        }

        // Event Delegation for options
        optionsListEl.addEventListener('click', (event) => {
            if (event.target && event.target.matches('li.option-item')) {
                // Check if the question has already been answered
                if (userAnswers[currentQuestionIndex] === null) {
                    const selectedIndex = parseInt(event.target.dataset.index, 10);
                    selectOption(selectedIndex);
                }
            }
        });

        prevBtn.addEventListener('click', goToPreviousQuestion);
        nextBtn.addEventListener('click', goToNextQuestion);
        hintBtn.addEventListener('click', showHint);
        
        // 初始加载
        loadQuestion();
      </script>
    </body>
    </html>
  